F. Mostafa

Prediction of Parkinson disease progression from sparse longitudinal trajectories using multiclass likelihood contrast learning

Background: Biomedical studies increasingly collect repeated measurements, such as clinical ratings, speech measures, gait summaries, and wearable-sensor features, at irregular subject-specific follow-up times. These data are often sparse and unaligned, making them difficult to use with standard classifiers that requir...